Search Results (148)

Legal requirements for minimum distances between vehicles are often not met for short periods of time, especially when changing lanes on multi-lane roads. These situations are typically non-hazardous, as human drivers anticipate surrounding traffic, allowing for shorter headways and improved traffic flow. Automated vehicles (AVs), however, are typically designed to maintain strict headway limits, potentially reducing traffic efficiency. Therefore, legal questions arise as to whether mandatory gap and headway limits for AVs may be violated during periods of non-compliance. While traffic flow simulation is a common method for analyzing AV impacts, previous studies have typically modeled AV behavior using driver models originally designed to replicate human driving. These models are not well suited for representing clearly defined, structured non-compliant maneuvers, as they cannot simulate intentional, rule-deviating strategies. This paper addresses this gap by introducing a concept for AV non-compliant behavior and implementing it as a module within a pre-existing AV driver model. Simulations were conducted on a three-lane highway with an on-ramp under varying traffic volumes and AV penetration rates. The results showed that, with an AV-penetration rate of more than 25%, road capacity at highway entrances could be increased and travel times reduced by over 20%, provided that AVs were allowed to merge with a legal gap of 0.9 s and a minimum non-compliant gap of 0.6 s lasting up to 3 s. This suggests that performance gains are achievable under adjusted legal requirements. In addition, the proposed framework can serve as a foundation for further development of AV driver models aiming at improving traffic efficiency while maintaining regulatory compliance. Full article

Port green spaces are essential protective barriers, enhancing safety and environmental resilience in high-activity port regions. Given the intensity of human activities in these areas, understanding the factors influencing the carbon sequestration capacity and ecological benefits of port green spaces is crucial for developing sustainable green ports. This study integrated field investigations and remote sensing data to estimate carbon density and carbon sequestration capacity in the Dongjiakou Port area, examining their relationship with port green space planning. The results indicated that carbon density in green spaces showed a significant negative correlation with the number of lanes in adjacent roads, where an increase in lane numbers corresponded to lower carbon density. Additionally, carbon density decreased significantly with increasing distance from the shipping center. In contrast, a significant positive correlation was observed between carbon density and distance from large water bodies, indicating that green spaces closer to large water bodies exhibited smaller carbon density. Infrastructure development in Dongjiakou substantially negatively impacted vegetation carbon sequestration capacity, with effects not reversible in the short term. However, green space enhancement efforts provided additional ecological benefits, leading to a 50.9 ha increase in green space area. When assessing carbon density in urbanizing areas, geographical influences should be prioritized. Furthermore, the long-term environmental impacts of urban expansion must be considered at the early planning stages, ensuring the implementation of proactive protective measures to mitigate potential ecological disruptions. Full article

Optimally configuring the number and turning functions of intersection approach and exit lanes to adapt to changing traffic demands, along with optimal traffic signal timing, is key to ensuring smooth, safe, and efficient urban road intersections. Compared to conventional “left-straight-right” lane configurations, non-conventional lanes have been widely adopted by various countries in recent years. This paper systematically reviews research progress on non-conventional lane design and control coordination optimization at urban road intersections, including operational mechanisms, applicable conditions, and optimization methods for various forms. By examining relevant research findings, the paper analyzes the effectiveness of non-conventional lanes in improving capacity, reducing delays, and enhancing safety. The research finds that although the application of non-conventional lanes has achieved positive results in practice, issues still exist, such as “practice outpacing theory,” “insufficient utilization of time-space resources,” and “incomplete safety evaluation.” Future research should focus on constructing a systematic evaluation framework, establishing demand-responsive dynamic lane function conversion mechanisms, developing refined and precise control methods with spatiotemporal coordination, and further exploring innovative applications of non-conventional lanes in connected and automated vehicle environments. The findings will provide theoretical and technical support for the scientific design and efficient operation of non-conventional lanes at urban road intersections. Full article

The motorized vehicle methodology in the Highway Capacity Manual (HCM) does not account for the effect of left-turn bay overflow, which is stated as a limitation of the methodology. In this study, an adjustment factor was developed to quantify the impact of left-turn bay length on the through lane capacity at signalized intersections. The adjustment factor was modeled based on a large number of scenarios generated using the CORSIM microsimulation model. These scenarios covered intersection geometries typical for two-phase signal control and included a wide range of traffic parameters (number of lanes, traffic volume, left-turn volume, left-turn bay length, cycle length, and green ratio). By comparing the capacity values obtained with a short left-turn bay to those with an infinitely long bay under identical other traffic conditions, it was possible to develop an adjustment factor that reflects the impact of turn bay overflow. A regression-based model was created and validated, showing very good agreement with the simulated values. The new adjustment factor provides an enhancement of the HCM estimation methodology that improves the accuracy of capacity and delay estimates in intersection evaluations as well as supports more effective intersection design and sustainable mobility. More accurate capacity estimation reduces congestion, travel delays, and vehicle stopping, directly contributing to sustainable transportation goals, lowering emissions, and supporting environmentally responsible urban mobility systems. Full article

Traffic congestion in urban areas presents significant challenges to mobility, road safety, and the overall quality of the urban traffic network. This study presents a simulation-based modeling framework for dynamic lane assignment (DLA) systems designed to optimize traffic flow on Vukovar Street in Zagreb, Croatia, which is an urban corridor where the existing infrastructure fails to meet capacity demands during peak morning and afternoon hours. Using real-time traffic data and the PTV VISSIM environment, an adaptive DLA model responsive to current traffic conditions was developed and evaluated. The proposed model improves traffic flow efficiency with minimal physical infrastructure changes, focusing on maximizing capacity within existing corridor constraints. The results of this research indicate that the proposed model reduces average vehicle delay by 21.4% and shortens queue lengths by 19%. The effectiveness of the DLA approach is evaluated through comparative analysis with traditional static traffic configurations, demonstrating significant improvements in traffic efficiency, reduced travel times, and enhanced network performance. While this study is limited to a simulation environment, it provides a strong foundation for future real-world applications and offers a practical approach to improving traffic network efficiency. Full article

This paper presents a microsimulation-driven framework to analyze the performance of connected and automated vehicles (CAVs) alongside vehicles with human drivers (VHDs), channeled towards assessing project alternatives in road intersection design. The transition to fully automated mobility is driving the development of new intersection geometries and traffic configurations, influenced by increasing market entry rates (MERs) for CAVs (CAV-MERs), which were analyzed in a microsimulation environment. A suburban signalized intersection from the Polish road network was selected as a representative case study. Two alternative design hypotheses regarding the intersection’s geometric configurations were proposed. The Aimsun micro-simulator was used to hone the driving model parameters by calibrating the simulated data with reference capacity functions (RCFs) based on CAV factors derived from the Highway Capacity Manual 2022. Cross-referencing the conceptualized geometric design solutions, including a two-lane roundabout and an innovative knee-turbo roundabout, allowed the experimental results to demonstrate that CAV operation is influenced by the intersection layout and CAV-MERs. The research provides an overview of potential future traffic settings featuring CAVs and VHDs operating within various intersection designs. Additionally, the findings can support project proposals for the geometric and functional design of intersections by highlighting the potential benefits expected from smart driving. Full article

The ecological restoration of oyster reef ecosystems enhances their ecological functions and strengthens carbon sequestration capacity in coastal zones. Identifying suitable restoration sites is a crucial prerequisite for initiating oyster reef restoration projects. This study developed an oyster reef restoration suitability index model for the Tianjin coast of Bohai Bay by integrating the Analytic Hierarchy Process (AHP) with the Geographic Information System (GIS). It was then applied to assess the region’s suitability for oyster reef restoration. The suitability analysis identified favorable environmental conditions for oyster reef restoration in most of the Tianjin coastal area, with high suitability for factors like dissolved oxygen, pH, and seabed slope. However, excessive water depth in the eastern bay mouth and strong currents in the southwestern region made these areas unsuitable. The northern and western coastal regions were deemed optimal restoration sites, while proximity to shipping lanes and industrial activities limited feasibility in some nearshore zones. The model outputs exhibited strong spatial concordance with existing oyster reef distributions, validating its predictive accuracy. This framework offers a robust foundation for oyster reef restoration planning, with an adaptable index system that allows for regional extrapolation. By leveraging this model, decision-makers can systematically evaluate site-specific restoration suitability, optimize resource allocation, and guide strategic conservation planning. Full article

This study investigates the structural performance and load-bearing capacity of single- and double-story modular bridge configurations using both experimental testing and finite element analysis. A full-scale field test was conducted on a 45.7 m double-story bridge subjected to truck loading at ten distinct positions along the span. Midspan deflections and axial strains of key members were measured and analyzed at each loading position to assess the bridge’s response under service loads. The experimental data were used to validate three-dimensional finite element (FE) models and refine modeling techniques for the double-story modular bridge. The validated FE models enabled further analysis of the structural performance of double-truss–double-story (DD) and quadruple-truss–single-story (QS) modular bridge configurations, both in single- and double-lane setups. The numerical results demonstrated that the double-story configuration with double truss lines per side provided a notable improvement in stiffness and load-carrying capacity compared to the single-story configuration with quadruple truss lines. Moreover, single-lane bridges exhibited better performance than their double-lane equivalents, emphasizing the impact of bridge width on structural stability. Wider, double-lane bridges were found to be more prone to out-of-plane buckling at midspan, with the top chords experiencing significantly greater deformation. Buckling analyses indicated that, although the DD and QS configurations had comparable critical loads, their failure mechanisms differed. Finally, live load factors predicted through the models were compared with the requirements of the Canadian Highway Bridge Design Code (CHBDC), confirming that the DD configuration in a two-lane setup meets code expectations and demonstrates effective structural performance. Full article

One of the key reasons why the road capacity of urban roads in China often fails to meet the designed capacity is the mixture of heavy vehicles (slow-moving) and light vehicles (fast-moving). This paper presents a two-lane cellular automaton model suitable for simulating urban road traffic that includes intersections, based on the NaSch model. The model comprehensively takes into account multiple key factors, such as vehicle safety distance, speed differences between adjacent vehicles, the acceleration and deceleration performance of different types of vehicles, and driver reaction time, enabling it to more realistically reproduce the complex characteristics of mixed traffic flows on urban roads. The paper investigates and analyzes the influence of traffic flow density and the proportion of heavy vehicles on the moving bottleneck effect in urban roads from several aspects, including space–time evolution diagrams, traffic flow, average speed, and lane-changing rates. The results indicate that the model established in this paper successfully simulates the characteristics of mixed traffic flows on urban roads, and the simulation results align with actual traffic conditions, achieving the expected simulation effects. Before the traffic volume reaches saturation, the higher the proportion of heavy vehicles on urban roads, the stronger the moving bottleneck effect. This confirms the necessity of conducting research on the phenomenon of moving bottlenecks and the mechanisms of traffic impacts in urban roads, providing a scientific basis for formulating effective traffic dispersion measures and alleviating traffic congestion in the future. This research possesses significant practical meaning and value. Full article

Sharing dedicated bus lanes with ridesharing private vehicles plays a positive role in improving road traffic efficiency and alleviating traffic congestion. This study investigates the willingness to adopt ridesharing and analyzes the factors influencing ridesharing decisions. Under the scenario of opening dedicated bus lanes to private ridesharing vehicles, a ridesharing decision-making model for dedicated bus lanes is established based on cumulative prospect theory. We analyze the impact of the bus-lane-sharing strategy on travelers’ ridesharing decisions and traffic flow structure. In addition, a bus lane operational efficiency evaluation model based on the combined weighting–TOPSIS method is constructed. Using the principle of maximum closeness, the operational efficiency of bus lanes is evaluated through a case study in a specific area of Nanchang City. The research results indicate that the closeness degree is 0.3720 without the bus-lane-sharing strategy, while the minimum closeness degree is 0.3744 and the maximum closeness degree is 0.3749 when the bus-lane-sharing policy is implemented. Therefore, the implementation of the bus-lane-sharing strategy demonstrates better operational efficiency compared to scenarios without sharing strategies. Additionally, when the number of ridesharing vehicles is relatively small and their capacity is large, travel costs are significantly reduced, and the overall road operational efficiency is improved. This study provides important reference values and practical significance for alleviating traffic congestion, improving the utilization efficiency of road resources, and formulating bus-lane-sharing policies. Full article

Numerous design cases of abandoning auxiliary lanes for freeway dual-lane ramps with low traffic volumes exist, adapting to complex engineering conditions and reducing construction costs, but the national specifications have not posed specific setup conditions for auxiliary lanes. Thus, this paper uses traffic flow theory and simulation tools to study the critical traffic conditions applicable to auxiliary lanes on dual-lane exit ramps of freeways. Initially, the vehicle operation data in the UAV (unmanned aerial vehicle) aerial video were extracted using an object detection algorithm. Subsequently, the VISSIM simulation calibration procedure was developed based on traffic flow theory and the orthogonal experimental method. The impact of auxiliary lanes on the capacity of the freeway diverging area was analyzed through the simulation results based on traffic flow theory. Eventually, the critical traffic conditions applicable to auxiliary lanes were proposed. The results show that the maximum traffic volume applicable to non-auxiliary lane designs decreases with increasing diverging ratios. The research findings define the application conditions for auxiliary lanes on dual-lane ramp exits, contributing to the sustainable development of transportation design and operations. The VISSIM simulation calibration procedure based on data collection and traffic flow theory developed in this paper also provides an innovative and sustainable approach to road design issues. Full article

The information interaction characteristics of connected vehicles are distinct from those of non-connected vehicles, thereby exerting an influence on the conventional traffic flow model. The original lane-changing model for non-connected vehicles is no longer applicable in the context of the new traffic flow environment. The modelling of the new hybrid traffic flow, comprising both connected and ordinary vehicles, is set to be a pivotal research topic in the coming years. The objective of this paper is to present a methodology for optimal mixed traffic flow dynamic modelling and cooperative control in intelligent and connected environments (ICE). The study utilizes the real-time perception and information interaction of connected vehicles for traffic information, taking into account the access characteristics of both connected and non-connected vehicles. The satisfaction-based free lane-changing and mandatory lane-changing models of connected vehicles are designed. Secondly, a mixed traffic flow lane-changing model based on influence characteristics is constructed for the influence area of connected vehicles. This model takes into account the degree of influence that connected vehicles have on non-connected vehicles, with different distances being considered respectively. Subsequently, a vehicle guidance strategy for mixed traffic flows comprising grid-connected and conventional vehicles is proposed. A variety of speed guidance scenarios are considered, with an in-depth analysis of the speed optimization of connected vehicles and the movement law of non-connected vehicles. This comprehensive analysis forms the foundation for the development of a vehicle guidance strategy for mixed traffic flows, with the overarching objective being to minimize the average delay of vehicles. In order to evaluate the effectiveness of the proposed method, the intersection of Gaota Road and Fangshui North Street in Yanqing District, Beijing, has been selected for analysis. The results of the study demonstrate that by modifying the density of the mixed traffic flow, the overall average speed of the mixed traffic flow declines as the density of vehicles increases. The findings reported in this study reflect the role of connected vehicles in enhancing road capacity, maximizing intersection capacity and mitigating the occurrence of queuing phenomena, and improving travel speed through the mixed traffic flow lane-changing model based on impact characteristics. This study also provides some guidance for future control of the mixed traffic flow formed by emergency vehicles and social vehicles and for realizing a smart city. Full article

As autonomous driving technology advances, connected and autonomous vehicles (CAVs) will coexist with human-driven vehicles (HDVs) for an extended period. The deployment of CAVs will alter traffic flow characteristics, making it crucial to investigate their impacts on mixed traffic. This study develops a hybrid control framework that integrates a platoon control strategy based on the “catch-up” mechanism with lane management for CAVs. The impacts of the proposed hybrid control framework on mixed traffic flow are evaluated through a series of macroscopic simulations, focusing on fundamental diagrams, traffic oscillations, and safety. The results illustrate a notable increase in road capacity with the rising market penetration rate (MPR) of CAVs, with significant improvements under the hybrid control framework, particularly at high MPRs. Additionally, traffic oscillations are mitigated, reducing shockwave propagation and enhancing efficiency under the hybrid control framework. Four surrogate safety measures, namely time to collision (TTC), criticality index function (CIF), deceleration rate to avoid a crash (DRAC), and total exposure time (TET), are utilized to evaluate traffic safety. The results indicate that collision risk is significantly reduced at high MPRs. The findings of this study provide valuable insights into the deployment of CAVs, using control strategies to improve mixed traffic flow operations. Full article

This work proposes a single regime speed–flow model to fit the speed–flow relationship on the M25, London’s main motorway which is recurrently congested, especially near Heathrow Airport. The proposed model had a better performance compared with the existing classic models. A whole year’s field data on various sites of the M25 motorway were collected by the National Highways MIDAS (Motorway Incident Detection and Automatic Signalling) system and analysed. The proposed model was fitter on both four-lane and lane-by-lane conditions than the existing models, in terms of lower relative error and RMSE values and higher R² values (minimum R² = 0.79), which means the proposed model captured the speed–flow relationship better. In addition, the proposed model was used to fit traffic characteristics under different weather conditions and decided the threshold of the CM algorithms using the Gaussian function. The results showed that both free-flow speed and road capacity were significantly reduced by up to 7% and 11%, respectively, under different rainfall conditions, and that congestion management should be triggered in advance on rainy days. Further analysis of extensive data over a wider space and time is required to test the transferability of these findings to other contexts. Full article

Freeway incidents block road lanes and result in increasing travel time delays. The intense lane changes of upstream vehicles may also lead to capacity drop and more congestion. Connected vehicles (CVs) offer a viable solution to minimize the impact of such incidents via monitoring the status of the incidents and providing real-time driving guidance. This paper evaluates the performance of an existing CV-enabled incident management system, which minimizes travel time by effectively leading CVs to bypass incident spots. This study comprehensively quantifies the effects of system parameters (speed weight and lane-changing inertia), control segment length, and road information-updating intervals. This analysis identifies the optimal settings for the incident management system to minimize vehicle travel time delays. Additionally, this paper evaluates the influence of CV market penetration rates (MPRs), network volume-to-capacity ratios, and incident settings to understand the system benefits under varying connected environments and traffic conditions. The results reveal that with the control of the proposed system, overall travel delays can be reduced by up to 45% and that road congestion caused by incidents can be mitigated quickly. Full article